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NMT

Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

Papers

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Showing 501–550 of 1773 papers

TitleStatusHype
Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine TranslationCode0
Fully Character-Level Neural Machine Translation without Explicit SegmentationCode0
Improved Neural Machine Translation with a Syntax-Aware Encoder and DecoderCode0
Benchmarking Machine Translation with Cultural AwarenessCode0
AFRIDOC-MT: Document-level MT Corpus for African LanguagesCode0
Encoder-Decoder Shift-Reduce Syntactic ParsingCode0
Morphologically-Guided Segmentation For Translation of Agglutinative Low-Resource LanguagesCode0
Prose2Poem: The Blessing of Transformers in Translating Prose to Persian PoetryCode0
ENCORE: Ensemble Learning using Convolution Neural Machine Translation for Automatic Program Repair—0
Encodings of Source Syntax: Similarities in NMT Representations Across Target Languages—0
Causal Transformers: Improving the Robustness on Spurious Correlations—0
Encoding Gated Translation Memory into Neural Machine Translation—0
Encoders Help You Disambiguate Word Senses in Neural Machine Translation—0
Categorizing Semantic Representations for Neural Machine Translation—0
Are BLEU and Meaning Representation in Opposition?—0
Enabling Multi-Source Neural Machine Translation By Concatenating Source Sentences In Multiple Languages—0
Empirical Evaluation of Active Learning Techniques for Neural MT—0
Capturing document context inside sentence-level neural machine translation models with self-training—0
Are BLEU and Meaning Representation in Opposition?—0
Empirical Analysis of Korean Public AI Hub Parallel Corpora and in-depth Analysis using LIWC—0
EMMeTT: Efficient Multimodal Machine Translation Training—0
Efforts Towards Developing a Tamang Nepali Machine Translation System—0
AR: Auto-Repair the Synthetic Data for Neural Machine Translation—0
Effort-Aware Neural Automatic Post-Editing—0
Efficient Unsupervised NMT for Related Languages with Cross-Lingual Language Models and Fidelity Objectives—0
Can the Variation of Model Weights be used as a Criterion for Self-Paced Multilingual NMT?—0
Efficient Transfer Learning for Quality Estimation with Bottleneck Adapter Layer—0
Efficient Technical Term Translation: A Knowledge Distillation Approach for Parenthetical Terminology Translation—0
Can Synthetic Translations Improve Bitext Quality?—0
A Pronoun Test Suite Evaluation of the English--German MT Systems at WMT 2018—0
A fine-grained error analysis of NMT, SMT and RBMT output for English-to-Dutch—0
Efficient Neural Machine Translation with Prior Word Alignment—0
Efficient Neural Machine Translation for Low-Resource Languages via Exploiting Related Languages—0
Can Synthetic Translations Improve Bitext Quality?—0
Efficient Inference for Multilingual Neural Machine Translation—0
Can NMT Understand Me? Towards Perturbation-based Evaluation of NMT Models for Code Generation—0
A Primer in NMTology: What we have understood about NMT—0
Efficient Bilingual Generalization from Neural Transduction Grammar Induction—0
Can Neural Machine Translation be Improved with User Feedback?—0
Effective Use of Target-side Context for Neural Machine Translation—0
Effective Parallel Corpus Mining using Bilingual Sentence Embeddings—0
Can Domains Be Transferred Across Languages in Multi-Domain Multilingual Neural Machine Translation?—0
A Preordered RNN Layer Boosts Neural Machine Translation in Low Resource Settings—0
Effectively pretraining a speech translation decoder with Machine Translation data—0
Convergences and Divergences between Automatic Assessment and Human Evaluation: Insights from Comparing ChatGPT-Generated Translation and Neural Machine Translation—0
EduMT: Developing Machine Translation System for Educational Content in Indian Languages—0
EdinSaar@WMT21: North-Germanic Low-Resource Multilingual NMT—0
Echo: Compiler-based GPU Memory Footprint Reduction for LSTM RNN Training—0
Echo State Neural Machine Translation—0
Calibration of Encoder Decoder Models for Neural Machine Translation—0
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